Streams serve as open windows for carbon emissions to the atmosphere due to the frequent supersaturation of carbon dioxide (CO2) and methane (CH4) that originates from large carbon input during runoff and associated in-stream processes. Due to the high spatial and temporal variability of the underlying environmental drivers (e.g., concentrations of dissolved CO2 and CH4, turbulence, and temperature), it has remained difficult to address the importance and upscale the emissions to annual whole-system and regional values. In this study, we measured concentrations and calculated emissions of CO2 and CH4 at diel and seasonal scales at 15 stations in a 1.4 km2 stream network that drains a mixed lowland catchment consisting of agriculture (210 km2), forest (56 km2), and lakes, ponds, and wetlands (22 km2) in the upper River Odense, Denmark to evaluate environmental drivers behind the spatiotemporal variability. We used automatically venting floating chambers to calculate hourly diffusive fluxes of CO2 and CH4 and CH4 ebullition. We found: 1) highly supersaturated CO2 and CH4 concentrations (median: 175 and 0.33 µmol L−1, respectively) and high diffusive fluxes of CO2 and CH4 (median: 3,608 and 19 µmol m−2 h−1, respectively); 2) lower daytime than nighttime diffusive emissions of CO2 in spring and summer, but no diel variability of CH4; 3) higher concentrations and emissions of CH4 at higher temperatures; and 4) higher emissions of CH4 at stations located in sub-catchments with higher agricultural coverage. Ebullition of CH4 peaked at two stations with soft organic sediment and low summer flow, and their ebullition alone constituted 30% of total annual CH4 emissions from the stream network. Mean annual CO2 emissions from the hydrological network (37.15 mol CO2 m−2 y−1) exceeded CH4 emissions 100-fold (0.43 mol CH4 m−2 y−1), and their combined warming potential was 1.83 kg CO2e m−2 y−1. Overall, agricultural sub-catchments had higher CH4 emissions from streams, while lakes and ponds likely reduced downstream CH4 and CO2 emissions. Our findings demonstrate that CO2 and CH4 emissions data at high spatial and temporal resolution are essential to frame the heterogeneous stream conditions, understand gas emissions regulation, and upscale to annual values for hydrological networks and larger regions.
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